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Large-Scale Evaluations of Curricular Effectiveness: The Case of Elementary Mathematics in Indiana

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Abstract

We use data from one of the few states where information on curriculum adoptions is available – Indiana – to empirically evaluate differences in performance across three elementary-mathematics curricula. The three curricula that we evaluate were popular nationally during the time of our study, and two of the three remain popular today. We find large differences in effectiveness between the curricula, most notably between the two that held the largest market shares in Indiana. Both are best-characterized as traditional in pedagogy. We also show that the publisher of the least-effective curriculum did not lose market share in Indiana in the following adoption cycle; one explanation is that educational decision makers lack information about differences in curricular effectiveness.

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File URL: http://economics.missouri.edu/working-papers/2011/WP1122_koedel.pdf
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Bibliographic Info

Paper provided by Department of Economics, University of Missouri in its series Working Papers with number 1122.

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Length: 40 pgs.
Date of creation: 14 Oct 2011
Date of revision: 31 Jan 2012
Handle: RePEc:umc:wpaper:1122

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Related research

Keywords: curricular effectiveness; math curricula; non-experimental methods; matching methods; education policy;

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References

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  1. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
  2. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
  3. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
  4. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
  5. Brian A. Jacob & Lars Lefgren & David Sims, 2008. "The Persistence of Teacher-Induced Learning Gains," NBER Working Papers 14065, National Bureau of Economic Research, Inc.
  6. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
  7. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
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Cited by:
  1. Cory Koedel & Rachana Bhatt & Douglas Lehmann, 2012. "Is Curriculum Quality Uniform? Evidence from Florida," Working Papers 1206, Department of Economics, University of Missouri.

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